import gradio as gr
from src.model.him_model import HIMModel
from config.model_config import HIMConfig
from config.environment_config import EnvironmentConfig

def initialize_model():
    model_config = HIMConfig()
    env_config = EnvironmentConfig()
    return HIMModel(model_config)

def chat(
    message: str,
    system_message: str = "You are a friendly Chatbot.",
    max_tokens: int = 512,
    temperature: float = 0.7,
    top_p: float = 0.95
):
    input_data = {
        "message": message,
        "system_message": system_message,
        "parameters": {
            "max_tokens": max_tokens,
            "temperature": temperature,
            "top_p": top_p
        }
    }
    
    result = model.generate_response(input_data)
    return result["response"]

model = initialize_model()

interface = gr.Interface(
    fn=chat,
    inputs=[
        gr.Textbox(label="Message"),
        gr.Textbox(label="System Message", value="You are a friendly Chatbot."),
        gr.Slider(minimum=1, maximum=2048, value=512, label="Max Tokens"),
        gr.Slider(minimum=0.1, maximum=1.0, value=0.7, label="Temperature"),
        gr.Slider(minimum=0.1, maximum=1.0, value=0.95, label="Top P")
    ],
    outputs=gr.Textbox(label="HIM Response"),
    title="Hybrid Intelligence Matrix (HIM)",
    description="Interact with the HIM system for advanced cognitive processing"
)

if __name__ == "__main__":
    env_config = EnvironmentConfig()
    interface.launch(
        server_name=env_config.api_host,
        server_port=env_config.api_port,
        enable_cors=env_config.enable_cors
    )